Spring 2019 Advanced Reporting
Rob Wells
1/22/2019
Inside Twitter: Data Analysis for Journalists
Jour 405v, Jour 5003, Spring 2019
Rob Wells, Ph.D.
University of Arkansas
School of Journalism and Strategic Media
@rwells1961
Course Goal: Students will learn the latest data journalism techniques that drive modern newsrooms and public relations / advertising offices. The class will extract and analyze Twitter data with the goal of producing an interactive multimedia presentation.
Course Description: This course will teach students how to code in programs such as R and SQL and how these powerful tools are used in modern news reporting. Quality reporting in newsrooms requires a solid foundation of data analysis. The data skills taught in this class are in high demand in newsrooms and corporations.
Required Text: Machlis, Sharon. Practical R for Mass Communications and Journalism. Chapman & Hall/CRC The R Series. 2018. ISBN 9781138726918 https://www.amazon.com/gp/search?keywords=9781138726918
Upon completion of this course, you will celebrate like this:
–
Week #1:Introduction and R Basics
Agenda: –1/14/2019 - Week 1
–Email to students
–Discuss syllabus
–Intro R and R Studio. Open program.
Machlis website:
http://www.machlis.com/R4Journalists/index.html
–R interface explained: Four main windows
Script writing, R Markdown, Table Viewer: Upper Left
Environment - data loaded in R: Upper Right
Console - write commands in R: Lower Left
File Manager and Html table viewer: Bottom Right
–Show basic R skills.
–Loading software. Tidyverse
Rio
–Conventions in coding.
–How many rows? nrow(yourdataset)
–How many columns? ncol(yourdataset)
–What is in the first five rows? head(yourdataset)
–rename columns. create columns
| ##Wednesday, Jan. 16 |
| –Misc |
| Class intros Book - Amazon Installation issues on laptops? Twitter feeds: @rstudiotips |
| –Run demos from Ch. 3 |
| –Show Collins results |
| –Twitter analysis of Trump Tweets http://varianceexplained.org/r/trump-tweets/ |
| –Ch 1 & 2 of Machlis: Key Points |
| Reproducible research Repetitive tasks in modern newsrooms. Employment reports, crime stats, budgets Variables - an R object Assignment operator <- Case sensitive Vector: A vector can only have one type of data - all integers, all strings Dataframe - like a spreadsheet Save files - Don’t save workspace: because all of your variables will be stored and re-loaded the next time you launch RStudio. It’s too easy to forget about previously stored variables that can interfere with later work, |
| –Software packages: tidyverse, rio, pacman |
 |
| –Software: How to get details and help |
| help(package=“dplyr”) browseVignettes(“NameOfPackage”) help(“NameOfFunction”) ??median |
| –Data Types and R |
| Machlis: 2.4.2 Data types you’re likely to use often |
 |
|
| –EXERCISES: Excel vs R –Load tutorial: Introduction-to-R-January-2019.R > Download this file and open it in R Studio |
| –Left click on the page, remove .txt extension, save as all files |
| –Keyboard Shortcuts |
| Tab - Autocomplete Control (or Command) + UP arrow - last lines run Control (or Command) + Enter - Runs current or selected lines of code in the top left box of RStudio Shift + Control (or Command) +P - Reruns previous region code |
| **Notes:** –Basic descriptive statistics —Review ComputerWorld’s Beginner’s Guide To R –Stack Overflow at stackoverflow.com |
| Reading: |
| –Machlis. Chapter 1 & 2. |
| –Beginner’s guide to R: https://www.computerworld.com/article/2497143/business-intelligence/business-intelligence-beginner-s-guide-to-r-introduction.html |
| –Twitter analysis of Trump Tweets http://varianceexplained.org/r/trump-tweets/ |
| –Review another R tutorial https://docs.google.com/presentation/d/1zICxR7qDM3RQ2Nxi5CqHlM3H8I7qoVkNtqcNcnbbDCw/edit#slide=id.p |
| Resources: RStudio Navigation Tricks You Might’ve Missed https://rviews.rstudio.com/2016/11/11/easy-tricks-you-mightve-missed/ |
| How Do I? https://smach.github.io/R4JournalismBook/HowDoI.html |
| Functions https://smach.github.io/R4JournalismBook/functions.html |
| Packages https://smach.github.io/R4JournalismBook/packages.html – |
Week #2 - 1/21/2019: File management
Wednesday, Jan. 23 Agenda
–Next week Quiz on Basic R functions described so far in exercises.
–Readings / Coursework for MA Students > Sign up for this free class from Nick Diakopolous
--Workload TBD - I will assign select videos and readings from this class. Exercise
–Load tutorial: Introduction-to-R-January-2019.R > Download this file and open it in R Studio
–Based on this tutorial, perform this exercise:
1. Percentage change from 2010-2017.
2. Produce a table with 5 counties with most growth.
3. Produce table with 5 counties with greatest population loss
4. Graph the top 5 and bottom 5
5. Filter just Benton County’s population for 2015
6. And if you finish that, bring up AOC.csv. How many rows? How many columns?
7. AOC.csv filter the text field for “Pelosi” or “Trump” or “New Deal"Reading:
–Machlis. Chapter 3 & 4.
–Study Twitter meta data
https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/tweet-object.html
–Look at this example: Ocasio.csv (in data folder of course page)
–Cohen, “Numbers in the Newsroom,” Common Mistakes.
–String data manipulation https://dereksonderegger.github.io/570L/13-string-manipulation.html
–Follow StoryBench, Northeastern Univ. https://twitter.com/storybench
Resources
–Use R instead of Excel: Andrew Ba Tran
Excellent Tutorial Spelling out Excel and Comparable Commands in R
https://trendct.org/2015/06/12/r-for-beginners-how-to-transition-from-excel-to-r/
Basic data work- head to http://bit.ly/excel_and_r
–All Cheat Sheets https://www.rstudio.com/resources/cheatsheets/
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Week #3- 1/28/2019: R Twitter Data. Data Types. Scripts
Monday, Jan. 28
–Quiz on Basic R functions for Wednesday The quiz will be multiple choice and will cover basic file management and data types, stuff I mentioned the first two weeks.
–Describe Assignment #1 due Feb. 6: Managing Data / Static Graphic
–Announcements
Blackboard site has web links for course
Agenda
–Continue with week #2 tutorial
–The course GitHub Page > Here it is
–See Data folder
Click AOC.csv
"View raw"
Cntl + click (or right click) - Save As - AOC.csv Exercise
–Loading Data from U.S. Census & Student Loans
–Load tutorial: Downloading Data 12-24-18.R
–Alternate download option: Use read.table() works for importing data:
–Loading and basic file management
Bringing in data
Data Frames
Extracting interesting details
Cleaning the data
Reshaping the format
Manipulating the data
Exporting
Add a column with a math conversion –Ch 3 & 4 of Machlis: Key Points
Ch 3 Exercises:
Stock chart exercise used quantmod is a library for financial analysis.
Median Income for a City
Loading packages
Ch 4 Importing Data
How read.table() works for importing data:
Loading data
Manipulating data: dplyr - stringr
Data Management: mutate rename bind_rows –Math –Summary Statistics
summary(Crime)
mean(x) Calculate the mean, or average, for variable x. median(x) Calculate the median. max(x) Find the maximum value. min(x) Find the minimum value. sum(x) Add all the values together. n() Count the number of records. Here there isn’t a variable in the brackets of the function, because the number of records applies to all variables. n_distinct(x) Count the number of unique values in variable x.
–Using a function for an equation
percent_change <- function(first_number, second_number) { pc <- (second_number-first_number)/first_number*100 return(pc) }
percent_change(100,150) [1] 50
This is what’s happening in the code above: * percent_change is the name of the function, and assigned to it is the function function() * Two variables are necessary to be passed to this function, first_number and second_number * A new object pc is created using some math calculating percent change from the two variables passed to it * the function return() assigns the result of the math to percent_change from the first line Build enough functions and you can save them as your own package.
–Set up column for math calculations Example: Total column shows winter snowfall in inches. To add a column showing totals in Meters, you can use this format:
.snowdata\(Meters <- snowdata\)Total * 0.0254
–Export data
Write Export output this file to a CSV or Excel write.csv or write.excel write.csv(AR2016_SMALL,“AR2016_SMALL.csv”)
Reading Machlis Chs. 5 & 6.
Seth C. Lewis, et al. “Big Data and Journalism: Epistemology, Expertise, Economics and Ethics,” Digital Journalism, 2015
Resources:
–For analysis library(dplyr)
Wednesday, Jan. 30
–Quiz on Basic R functions
–Data Visualization Intro
–Load tutorial: Basic Data Visualization 12-26-18.R
–Visualizing data
ggplot2 - charts and maps
Export Static chart Exercises
Basic Data Visualization 12-26-18.R
Questions on First Assignment
–Here is a good question that came in today about the first assignment.
Question:
``“What the hell? I converted population to numeric and the calculations come out as NA values! This is driving me insane! What is going on?”
Answer:
One of the obnoxious things about R is it considers commas as text. So it will show 720 as a number but 2,810 as not a number for calculations because it has a friggin comma.
Never fear. There is a solution. Run the find and replace function, called gsub
Crimedata\(Population <- gsub(",", "", Crimedata\)Population)
Translation:
#####Crimedata\(Population -- is the population column in your crime dataset #####gsub(",", "", finds a comma and replaces it with nothing. -- and it found the comma in the column Crimedata\)Population) and the <- dumps the results back into the Crimedata$Population column.
Fancy!
Question: “How do I get rid of the last row that only has text in the table that I just imported?”
Answer: #Get rid of row using base R commands
#####Crimedata <- Crimedata[-c(187), ]
Translation:
#####Crimedata[-c(187), ] looks for row #187, which has this garbage text, and gives it the big minus sign, which eliminates it.
#####Crimedata <- dumps this slimmed down table back into your table and so you are good to go.
–
Week #4 - 2/4/2019: Using R to build basic graphs and charts
Monday, Feb. 4
Agenda
–Assignment #1 due Feb. 6: Managing Data / Static Graphic
–GGplot –Work with sample Twitter data
–Conventions in coding
–Visualizing data
ggplot2 - charts and maps
htmlwidgets - web visualization interactives
plotly - exporting charts online
ChartExercises –Continue with Basic Data Visualization Exercise questions
–Dplyr Presentation
–DPLYR
Five basic verbs • filter() • select() • arrange() • mutate() • summarize() plus group_by() 
–Pipes - a Much-Used Command to Link Filters, Functions
pipe %>%
CMD + Shift + M –Presentation from Bob Rudis on Writing Readable Code with Pipes, delivered at the rstudio::conf 2017.
https://www.rstudio.com/resources/videos/writing-readable-code-with-pipes/
Pipes as a way of chaining commands.
object %>% operation() —> result
–GGPLOT –A handy explanation of ggplot and its components
If you’re using ggplot: plus it! For everything else: pipe it!
So geom_point() geom_bar() geom_boxplot()
–Key Concepts - Moving Forward:
Dplyr: Filters, Grouping, Sorting, pipes %>%
Pipe shortcut = CMD + SHIFT + M
Basic data visualization
Tidyverse
Work with sample Twitter dataNotes
–Data Wrangling-Text Mining in Twitter.
See entire scraping sequence. Extract from Twitter.Additional Exercises
–Ch. 3.8 Run a remote script to make an interactive map
–Median Income For City.R
–Work with sample Twitter data
–Other Topics
–Setting up an R Workflow –Twitter Metadata
–Work with sample Twitter data –Lubridate
Ch 3 Exercises: Stock chart exercise used quantmod is a library for financial analysis. dygraphs creates interactive Web graphics of data over time.
Notes
–How Do I? https://smach.github.io/R4JournalismBook/HowDoI.html
Resources
Basic Charts in R
https://www.youtube.com/watch?v=1EUJ0tsVsUA&t=12s
Reading
Machlis Chs. 7 & 8.
Transforming and Analyzing Data dplyr.pdf, Andrew Ba Tran, Washington Post
Charts_with_ggplot by Andrew Ba Tran,
Washington Post–
Wednesday, Feb. 6
–Note: Dr. Wells will be late - 10 a.m. - due to data mining presentation
–Begin class by working on XXXX exercise
–GGplot Video from Andrew Ba Tran
https://www.youtube.com/watch?v=Sx7d7eGRSj0&t=9s
Exercises
Basic crime rate in R exercise.txt Basic-Chart-January-2018.R
Twitter Metadata
Work with sample Twitter data
Week #5: Using R to build basic graphs and charts
Agenda –2/11/2019 - Week 5
–Themes for data viz library(ggthemes)
—-Work with sample Twitter data
–Terminology
ggplot
aes**Resources*
Grammar of Graphics http://vita.had.co.nz/papers/layered-grammar.html
–Graphing GGplot 12-28.R Exercises from Machlis Ch. 9. Facets
Notes –The pie chart focuses the reader on large percentages, and encourages the reader to think of the total –The stacked bar plot provides the same information, but makes it easier to accurately determine at a glance how large each group is out of the whole. –This bar chart splits the categories horizontally, and draws attention to how the family members are ordered. It encourages the reader to think about the distribution rather than disconnected categories, and gives a better sense of sense of scale.
Reading:
Machlis Chs. 9 & 10
Albert Cairo, “The Functional Art,” Principles of Data Visualization.
–Read Kavanaugh text mining story: Text analysis of Brett Kavanaugh’s opinion.
http://www.storybench.org/bringing-textual-analysis-tools-to-judge-brett-kavanaughs-latest-opinion/
For working with dates library(lubridate) Dealing-with-dates.pdf by Andrew Ba Tran
Samantha Sunne, “The Challenges and Possible Pitfalls of Data Journalism, and How You Can Avoid Them,” American Press Institute, 2016
Exercises
–Create R Markdown document, export to PDF, HTML
–Class Exercise - Graphing and Grouping Data Viz Exercise 2 From Ch 9 –
Week #6: GitHub
Agenda –2/18/2019 - Week 6
–Create a GitHub account. https://github.com/
–Follow this tutorial https://guides.github.com/activities/hello-world/
This class is intended to teach you modern workflow techniques for coding. A centerpiece of that workflow is GitHub. This is a website with a system that allows you to collaborate with other programmers on coding projects. It manages versions of software code and is a very popular with the tech elite.
Your GitHub account, which is public, represents an important professional image. Prospective employers and collaborators will look at your GitHub account.
–Andrew Ba Tran Tutorials on GitHub Git and Github Pages http://learn.r-journalism.com/en/git/
Installing Git https://journalismcourses.org/courses/RC0818/installing_git.pdf
GIT https://journalismcourses.org/courses/RC0818/git.pdf
Connecting to Github https://journalismcourses.org/courses/RC0818/github.pdf http://learn.r-journalism.com/en/git/github/github/
Best Practices for Github http://learn.r-journalism.com/en/git/github_pages/github-pages/
–Loading and basic file management
Commit
Branch
Pull Request
Fork Resources on GitHub
–GitHub flow
https://guides.github.com/introduction/flow/
–GitHub Guides
https://guides.github.com/
–Another GitHub guide
https://andrewbtran.github.io/NICAR/2018/workflow/docs/03-integrating_github.html
Reading:
Machlis Chs. 11 & 12
Installing Git for a Mac - Andrew Ba Tran
Exercises
Pair up.
Team 1 takes this code. Make changes.
Team 2 forks the code. Makes changes.
Pull & Commit –Setting up an R Workflow http://learn.r-journalism.com/en/publishing/workflow/r-projects/
Workbooks, Markdown –
Week #7: Twitter
Agenda –2/25/2019 - Week 7
–Due Feb 27: Assignment #2. Visualization of Twitter data
–Analyzing Tweets from public officials. Dataset TK
–Study Twitter meta data
https://twittercommunity.com/ https://developer.twitter.com/en/docs
–Register as Twitter Developer https://developer.twitter.com/en/account/get-started
Reading Machlis Chs. 13 & 14.
Twitter meta data
Resources:
Exercises
–
Week #8: R Markdown
Agenda –3/4/2019 - Week 8
–Quiz on GitHub –R Markdown
–R Markdown, Desktop Publishing –Andrew Ba Tran - Week 5 Publishing http://learn.r-journalism.com/en/publishing/ –R Markdown http://learn.r-journalism.com/en/publishing/rmarkdown/rmarkdown/ –More R Markdown http://learn.r-journalism.com/en/publishing/more_rmarkdown/more-rmarkdown/
–Rendering html as an output in GitHub
https://rmarkdown.rstudio.com/lesson-9.html https://github.com/rstudio/cheatsheets/raw/master/rmarkdown-2.0.pdf
–R Markdown Formatting
Sizing images: <.img src=“drawing.jpg” alt=“drawing” width=“200”/>
(Note: Remove the period before “img”) https://rpubs.com/RatherBit/90926
–Terminology
Render
Html
Markdown Notes R Markdown
This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.
When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:
summary(cars)## speed dist
## Min. : 4.0 Min. : 2.00
## 1st Qu.:12.0 1st Qu.: 26.00
## Median :15.0 Median : 36.00
## Mean :15.4 Mean : 42.98
## 3rd Qu.:19.0 3rd Qu.: 56.00
## Max. :25.0 Max. :120.00Including Plots
You can also embed plots, for example:
Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.
Reading
Machlis Chs. 15 & 16
Resources:
Exercises
Line breaks: Use HTML tags. Adding
will give a single line break – option for when two-space indentation is ignored.
–
Week #9: Text Mining
Agenda –3/11/2019 - Week 9
–Extra Grad Assignment - Scraping Twitter. Due March 13.
–Basic text mining techniques
–Lubridate
Reading Machlis Chs. 17 & 18
Resources:
–Joining Dataframes in R
https://www.youtube.com/watch?v=gLg4D9bMIyc&t=13s
–Data Wrangling http://learn.r-journalism.com/en/wrangling/
http://learn.r-journalism.com/en/wrangling/dplyr/dplyr/
https://github.com/r-journalism/learn-chapter-3/blob/master/dplyr/pipes-dplyr.R
Exercises Data Wrangling-Text Mining in Twitter.R
–
SPRING BREAK – March 18-22 – MAKE GOOD LIFE CHOICES
.
Week #10: Mapping in R
You will make this in the class
Agenda –3/25/2019 - Week 10
–Due March 27: Assignment #3. Interactive Map
–Produce a basic interactive map in R, post on WordPress
–Andrew Ba Tran - Week 4 Mapping http://learn.r-journalism.com/en/mapping/
Reading “Connecting the Dots” by Jacob Harris (2015) and discuss how people should or should not be represented through news visualizations.
What is code? http://www.bloomberg.com/graphics/2015-paul-ford-what-is-code/
Resources: –Visual Narrative Tricks by Albert Cairo https://www.youtube.com/watch?v=TSGaueL4Ggk
Spatial data maptools - work with shapefiles
Exercises –Maps in R 12-28-18.R
–
Week #11: Mapping in R
Agenda –4/1/2019 - Week 11
–Produce a basic interactive map in R, post on WordPress
–You will make this in the class
Reading Bad data visualizations. Data Translation.
The Journalist as Programmer: A Case Study of The New York Times Interactive News Technology Department http://isoj.org/wp-content/uploads/2016/10/ISOJ_Journal_V2_N1_2012_Spring.pdf
Resources:
Exercises –Maps Spatial Analysis Tutorial.R –
Week #12: Web Scraping in R
Agenda –4/8/2019 - Week 12
–Web Scraping in R
–Application Programming Interface - API
Twitter historical API https://developer.twitter.com/en/docs/tutorials/choosing-historical-api
–See 4.8 in Machlis: ‘Scrape’ data from Web pages with the rvest package and SelectorGadget browser extension or JavaScript bookmarklet. SelectorGadget helps you discover the CSS elements of data you want to copy that are on an HTML page; then rvest uses R to find and save that data. This is not a technique for raw beginners, but once you’ve got some R experience under your belt, you may want to come back and re-visit this. I have some instructions and a video on how to do this at http://bit.ly/Rscraping. RStudio has a webinar available on demand as well, at https://www.rstudio.com/resources/webinars/extracting-data-from-the-web-part-2/ .
Reading Julia Angwin, Terry Parris Jr., Surya Mattu. “Breaking the Black Box: What Facebook Knows About You,” ProPublica, 2016;
Nicholas Diakopolous, “Algorithmic Accountability,” Digital Journalism, 2014.
APIs - basics https://medium.com/@LewisMenelaws/a-beginners-guide-to-web-apis-and-how-they-will-help-you-23923a0da450
A gentle introduction to APIs for data journalists https://trendct.org/2016/12/29/fetching-airport-delays-with-python-a-gentle-guide-to-apis-for-journalists/
MA Students –Sign up for a Census API key: https://api.census.gov/data/key_signup.html
Resources:
Exercises –MA Students, Census API exercise –
Week #13: Web Scraping in R
Agenda –4/15/2019 - Week 13
– Web Scraping in R
Reading –Twitter analysis of Trump Tweets http://varianceexplained.org/r/trump-tweets/
Different types of Twitter APIs https://developer.twitter.com/en/products/products-overview
Amy Webb future of journalism trends https://futuretodayinstitute.wetransfer.com/downloads/0e84e883e140bafe9a3436a6464032be20171003123607/ecda17 Resources:
Exercises Continue with Week 12 materials
–
Week #14: Sentiment Analysis - Final Project
Agenda –4/22/2019 - Week 14
–Sentiment Analysis
Reading –Sentiment analysis http://saifmohammad.com/WebPages/NRC-Emotion-Lexicon.htm
–Saif Mohammad research on sentiment analysis
http://saifmohammad.com/index.html
Resources:
Exercises
Collins sentiment analysis 10-13-18.R
–
Week #15: Wrap Up
Agenda –4/29/2019 - Week 15
–Assignment #4 Final Project: Interactive Data Visualization
–
RESOURCES
Download R and RStudio
This program is loaded on all of the computers in Kimpel 146. You can load it on your laptop as well. It is not large and doesn’t tax the memory a lot. R runs on Windows, Mac and Linux, but this course uses the Mac version. If you use Windows on your personal laptop, the instructor is not responsible for any variations in the lessons and instructions.
First, download the most recent version of R at https://www.r-project.org/, . Look for the link to download R. Click that download option and you should be taken to CRAN, the Comprehensive R Archive Network, and a list of CRAN servers, called mirrors, around the world. Pick a server and choose the precompiled binary distribution for your operating system. Once the file finishes downloading, install it like any other software program – run the .exe for Windows or .pkg for Mac.
Accept all of the default settings for Mac.
Second, install RStudio, an excellent user interface that helps you manage and create R code. Download the open source edition of R Studio desktop and follow the prompts to install it. http://www.rstudio.com/products/rstudio/download/
More information: http://www.machlis.com/R4Journalists/download-r-and-rstudio.html